Iris authentication device, iris authentication method, and recording medium

ABSTRACT

The disclosure is inputting a first image captured an image of an authentication target; inputting a second image captured an image of a right eye or a left eye of the target; determining whether the second image is of a left eye or a right eye of the target based on information including the first image, and outputting a determination result as left/right information in association with the second image; detecting an overlap between a region including the second image and a predetermined region in the first image; calculating a verification score by comparing characteristic information that are related to the left/right information with iris characteristic information calculated from the second image, and calculating a first weighted verification score obtained by weighting the verification score with a detection result; and authenticating a target in the second image based on the first weighted verification score, and outputting an authentication result.

The present application is a Continuation application of Ser. No.17/283,050 filed on Apr. 6, 2021, which is a National Stage Entry ofPCT/JP2018/038396 filed on Oct. 16, 2018, the contents of all of whichare incorporated herein by reference, in their entirety.

TECHNICAL FIELD

The example embodiments relates to an iris authentication device and thelike for authenticating a target.

BACKGROUND ART

Personal authentication based on an individual difference of a livingbody (biometrics-based authentication) has a lower risk of leakage andtheft than a password or the like created by a user. Therefore, for thepurpose of identifying individuals and confirming rights, and for thepurpose of protecting security, a case of introducing individualauthentication based on an individual difference of a living bodyincreases. As a personal authentication technology based on anindividual difference of a living body, there is known a technologyusing a fingerprint, a vein, a face, an iris, voice, or the like asbiometric information.

Among them, iris authentication has high authentication accuracy. Thereason for this is because an iris pattern is more complicated than afingerprint, and is certainly different for every person. Furthermore,once an iris pattern is completed, there is no change or deteriorationthereafter. Unlike a fingerprint, an iris pattern can be recognizedwithout contact, and forgery is difficult. In addition, even the sameperson has a different iris pattern between the right eye and the lefteye.

However, when the iris authentication is performed, since an irispattern is different between the right eye and the left eye as describedabove, it is necessary to identify the left and right eyes. For thisidentification, for example, there is a technique for identifying theleft and right eyes by using a shape of an inner corner of the eye nearthe iris (see PTL 1). In addition to this, PTL 2 discloses a techniquerelated to an iris authentication device.

CITATION LIST Patent Literature

-   [PTL 1] JP 2005-227933 A-   [PTL 2] WO 2009/016846 A

SUMMARY Technical Problem

However, it is not always possible to identify left and right eyes onthe basis of an inner corner of the eye, which is a part of the face.For example, at a time of capturing an image of a face of a user to beauthenticated, it may not be possible to accurately capture an image ofthe inner corner of the eye when dark shadows appear on the face, stronglight is applied on the face, a shape of the inner corner of the eyechanges depending on a facial expression, or the inner corner of the eyeis covered by hair or glasses, and the like. Further, in order tocapture an image of the inner corner of the eye in detail from adistance, a telephotographic camera with a high magnification and animage analyzing apparatus with high accuracy are required, whichincreases cost.

The disclosure has been made in view of the above problems, and oneobject is to provide an iris authentication device and the like forperforming iris authentication with high accuracy by reliablyidentifying left and right eyes.

Solution to Problem

In view of the above problems, an iris authentication device accordingto a first aspect of the disclosure includes:

a first image input means for inputting a first image obtained bycapturing an image of an authentication target that moves in a specificdirection;

a second image input means for inputting, for at least one eye, a secondimage obtained by capturing an image of a right eye or a left eye of thetarget;

a determination means for determining whether the second image is of aleft eye or a right eye of the target on the basis of informationincluding the first image, and outputting a determination result asleft/right information in association with the second image;

a detection means for detecting an overlap between a region includingthe second image and a predetermined region in the first image;

a storage means for storing iris characteristic information of a righteye and a left eye relating to one or more targets to be authenticated;

a score calculation means for calculating a verification score bycomparing iris characteristic information calculated from the secondimage associated to the left/right information, with one or more piecesof characteristic information that are stored in the storage means andrelated to the left/right information, and calculating a first weightedverification score obtained by weighting the calculated verificationscore with a result of the detection; and

an authentication means for authenticating a target captured in thesecond image on the basis of the calculated first weighted verificationscore, and outputting an authentication result.

An iris authentication method according to a second aspect of thedisclosure includes:

inputting a first image obtained by capturing an image of anauthentication target that moves in a specific direction;

inputting, for at least one eye, a second image obtained by capturing animage of a right eye or a left eye of the target;

determining whether the second image is of a left eye or a right eye ofthe target on the basis of information including the first image, andoutputting a determination result as left/right information inassociation with the second image;

detecting an overlap between a region including the second image and apredetermined region in the first image;

calculating a verification score by comparing one or more pieces ofcharacteristic information that are related to the left/rightinformation and acquired from a storage means for storing irischaracteristic information of a right eye and a left eye relating to oneor more targets to be authenticated, with iris characteristicinformation calculated from the second image associated to theleft/right information, and calculating a first weighted verificationscore obtained by weighting the calculated verification score with aresult of the detection; and

authenticating a target captured in the second image on the basis of thecalculated first weighted verification score, and outputting anauthentication result.

An iris authentication program according to a third aspect of thedisclosure causes a computer to enable:

inputting a first image obtained by capturing an image of anauthentication target that moves in a specific direction;

inputting, for at least one eye, a second image obtained by capturing animage of a right eye or a left eye of the target;

determining whether the second image is of a left eye or a right eye ofthe target on the basis of information including the first image, andoutputting a determination result as left/right information inassociation with the second image;

detecting an overlap between a region including the second image and apredetermined region in the first image;

calculating a verification score by comparing one or more pieces ofcharacteristic information that are related to the left/rightinformation and acquired from a storage means for storing irischaracteristic information of a right eye and a left eye relating to oneor more targets to be authenticated, with iris characteristicinformation calculated from the second image associated to theleft/right information, and calculating a first weighted verificationscore obtained by weighting the calculated verification score with aresult of the detection; and

authenticating a target captured in the second image on the basis of thecalculated first weighted verification score, and outputting anauthentication result.

The iris authentication program may be stored in a recording medium.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is an example diagram of a configuration of an irisauthentication device according to a first example embodiment of thedisclosure.

FIG. 2 is an example view of an image of a target user moving in aspecific direction.

FIG. 3 is an example view of a first image and a second image acquiredfrom the image of the target user.

FIG. 4 is an example view of the second image associated with left/rightinformation.

FIG. 5 is an example view of a face template to be applied to the targetuser.

FIG. 6 is an example view showing a first image region divided into aplurality of rectangular regions.

FIG. 7 is an example view showing an overlap degree between the facetemplate and the first image region.

FIG. 8 is an example view showing an overlap degree between the facetemplate and the first image region.

FIG. 9 is an example view showing an overlap degree between the facetemplate and the first image region.

FIG. 10 is a flowchart showing an operation of the iris authenticationdevice according to the first example embodiment of the disclosure.

FIG. 11 is a diagram showing a configuration example of an irisauthentication device according to a second example embodiment of thedisclosure.

FIG. 12 is a view showing a configuration example of data stored in astorage unit.

FIG. 13 is a flowchart showing an operation of the iris authenticationdevice according to the second example embodiment of the disclosure.

FIG. 14 is a diagram showing a configuration example of an irisauthentication device according to a third example embodiment of thedisclosure.

FIG. 15 is a flowchart showing an operation of the iris authenticationdevice according to the third example embodiment of the disclosure.

FIG. 16 is a diagram showing a configuration example of an irisauthentication device according to a fourth example embodiment of thedisclosure.

FIG. 17 is a view showing a configuration example of data stored in anauthentication result storage unit.

FIG. 18 is a view showing an example of a change in light in the firstimage.

FIG. 19 is a flowchart showing an operation of the iris authenticationdevice according to the fourth example embodiment of the disclosure.

FIG. 20 is a configuration diagram of an information processingapparatus usable in the first to fourth example embodiments.

EXAMPLE EMBODIMENT

Hereinafter, each example embodiment will be described in detail withreference to the drawings. In the description of the drawings below,same or similar reference numerals are given to same or similar parts.However, the drawings schematically illustrate a configuration in theexample embodiments. Further, the example embodiments described beloware merely examples, and may be modified as appropriate to the extent ofbeing essentially the same.

First Example Embodiment

Examples of information for biometric authentication include a pluralityof pieces of information such as an ultrasound graph, an image of aliving body, or audio data. In the following description, an image(specifically, an iris image) are mainly used as an example, but this isnot intended to limit the example embodiments.

In each example embodiment, an authentication target is mainly a livingbody, and includes a person (a user), an animal, and the like. As theauthentication target, a thing other than the living body, such as amannequin, for example, may be included. When iris authentication isperformed, left and right eyes (including artificial eyes for thepurpose of impersonation) of the target are authenticated. In thefollowing description of the example embodiments, the authenticationtarget is also referred to as a “target user”.

(Iris Authentication Device)

As shown in FIG. 1, an iris authentication device 100 includes a firstimage input unit 11, a second image input unit 12, a determination unit13, a detection unit 14, a storage unit 15, a score calculation unit 16,and an authentication unit 17.

The first image input unit 11 and the second image input unit 12 areconnected to a camera 10. The camera 10 is a camera to capture an imageof a user to be authenticated. There may be one or a plurality ofcameras 10. The camera 10 captures an image of a user moving in aspecific direction. Moving in a specific direction means, for example,that the user walks from an entrance gate to an exit gate of anauthentication execution area, in a case of walk-through authentication(referring to performing biometric authentication while anauthentication target user is moving without stopping). The user movingin a specific direction is captured by the camera 10 as an image shownin FIG. 2, for example. Although an image of a whole body is captured inFIG. 2, this may be an image of a face or the like. The camera 10 isfixed at a position where the image as shown in FIG. 2 can be captured(a wall, a gate, or the like). Among the images captured by the camera10, image data of a region including the whole body of the user isinputted as a first image to the first image input unit 11, while imagedata of a region including a periphery of left and right eyes of theuser is inputted as a second image to the second image input unit 12.Processing for selecting the image region may be performed by the firstimage input unit 11 and the second image input unit 12 that havereceived the image from the camera 10. After the camera 10 performs theprocessing, the first image input unit 11 and the second image inputunit 12 may input the image of the selected image region.

The first image input unit 11 inputs, from the camera 10, the firstimage (see FIG. 3) obtained by capturing, at a particular location, animage of the region including the whole body of the user moving in thespecific direction. The first image may be a face image of the user.

The second image input unit 12 inputs, from the camera 10, the secondimage (see FIG. 3) obtained by capturing an image of at least one of aright eye and a left eye of the user moving in the specific direction.The second image input unit 12 preferably inputs an image for both eyes.However, if the camera 10 is unable to obtain an image of one eye (forexample, such as being unable to capture an image due to blocking withbangs or being unable to capture an image due to reflection of glasses),an image is captured for the other eye that can be captured. In FIG. 3,as an example, the camera 10 uses a region of the right and left eyes inthe whole body image (the first image) of the user to be captured as thesecond image, but the region of the left and right eyes may be magnifiedby a telephoto lens and captured.

The determination unit 13 determines whether the second image is of theleft eye or the right eye of the user on the basis of informationincluding the first image, and outputs left/right information indicatinga determination result in association with the second image (see FIG.4). As will be described later, the determination unit 13 outputs animage of an iris part as shown in FIG. 4. In the example embodiment, oneof the following two methods is used as an example of the determinationof the left and right eyes. As a first method, the determination unit 13determines whether the second image is of the left eye or the right eyeof the user by applying, in a region of the user's face in the firstimage, a predetermined template for detecting a contour of the face anda positional relationship of both eyes and the like to perform matchingprocessing, and specifying a region including the left eye and the righteye of the target user. In order to detect the positional relationshipof both eyes, the user's face needs to face a front side with respect tothe camera 10. However, by setting the camera 10 in advance at aposition where the image of the user moving toward a predeterminedtraveling direction can be captured, the user facing the front side withrespect to the camera 10 can be inevitably made a target of thedetermination. As a second method, the determination unit 13 determineswhether the second image is relevant to the left eye or the right eye ofthe user, by comparing a pixel in a region of right and left eyes of theuser in the first image with a pixel in a region of right or left eye ofthe user in the second image. In this case, as shown in FIG. 3, thedetermination unit 13 extracts a pixel of each region of right eye andthe left eye of the user in the first image, which is an image of awhole body, and compares the extracted pixels with a pixel in a regionof eye captured in the second image, and determines which of the rightand left eyes is captured in the second image in accordance with thesimilarity of the compared pixels. For the comparison of pixels, acontour tracking algorithm using a chain code, a principal componentanalysis method, a three-dimensional phase only correlation, or the likemay be used. A method of determining the left and right eyes is notlimited to the above methods.

Meanwhile, the first image and the second image may be captured at thesame timing by using two cameras 10. At this time, the camera to capturean image of the second image may be a telephoto camera capable ofcapturing an image with a high magnification. Further, the first imageand the second image may be captured at different timings by using thesame camera 10. At this time, it is preferable that the camera 10 canquickly switch the magnification of the telephoto function for capturingthe first image and the second image of the subject.

The detection unit 14 detects an overlap between a region including thesecond image and a predetermined region in the first image. For example,the camera 10 fixed at a certain place captures an image of the user.Here, the determination unit 13 applies, to the first image, a facetemplate for determining positions of the left and right eyes from thecontour of the user's face and the like, and specifies a region (theregion including the second image) including the left eye and the righteye of the target user included in the first image. In the example shownin FIG. 5, in the face template in the first image, the specified regionincluding the right eye of the target user is a, and the specifiedregion including the left eye of the target user is b. It is assumedthat the first image is divided in advance into rectangular regions asshown in FIG. 6 by a designer or the like. At this time, when the camera10 at the predetermined position captures an image of the moving targetuser, it is presumed that the right eye is included in a rectangularregion B2 and the left eye is included in a rectangular region B3, andthe regions are set in advance (these rectangular regions are set aspredetermined regions in the first image). This can be achieved, forexample, by causing a machine learning engine to learn a plurality ofimages of the target user at a certain position as teacher data inadvance. In this example, as shown in FIG. 6, it is assumed that, as aresult of learning, the region of the right eye of the target user shownin the first image is included in the rectangular region B2, and theregion of the left eye is included in the rectangular region B3. In thiscase, as shown in FIG. 7, the detection unit 14 superimposes the facetemplate and the divided first image, and detects whether the region aof the right eye in the face template overlaps with the rectangularregion B2 where the right eye should be present in the first image, andsimilarly detects whether the region b of the left eye in the facetemplate overlaps with the rectangular region B3 where the left eyeshould be present in the first image. The detection unit 14 outputs, asa detection result, to the score calculation unit 16 that the left andright eyes overlap at an appropriate position. When no overlap isdetected, for example, when the left and right eyes of the face templateoverlap with only a part of the rectangular region (B2, B3) where theleft and right eyes should be present in the first image (see FIG. 8),or when the image of the target user is small and the face template andthe rectangular region (B2, B3) do not overlap at all (see FIG. 9), thedetection unit 14 outputs, as a detection result, to the scorecalculation unit 16 that the left and right eyes do not overlap at anappropriate position.

The storage unit 15 stores iris characteristic information of a righteye and iris characteristic information of a left eye, of a plurality ofusers. Meanwhile, the iris characteristic information is, for example,an iris code (see characteristic information of FIG. 12) generated onthe basis of the Daugman's algorithm.

The score calculation unit 16 calculates the iris characteristicinformation from the second image (see FIG. 4) associated with theleft/right information, and calculates a first weighted verificationscore obtained by weighting the calculated verification score with adetection result. As an example, a case of using an iris code as theiris characteristic information will be described. The score calculationunit 16 specifies a boundary line of an iris from an image of the irisreceived from the determination unit 13, to extract an iris part.Further, the score calculation unit 16 applies a two-dimensional Gaborfilter to information of the extracted iris part to encode an irispattern, and generates an iris code. The iris code is, for example, a2048 bit digital encoding code.

Here, the second image associated with the left/right information refersto an iris image determined to be the right eye by the determinationunit 13 and tagged as “right eye”, or an iris image determined to be theleft eye by the determination unit 13 and tagged as “left eye” (see FIG.4). The iris code may be tagged with any one of the left and right eyes.

The score calculation unit 16 compares the calculated characteristicinformation with characteristic information of a plurality of usersrelated to the left/right information stored in the storage unit 15.Specifically, the score calculation unit 16 compares with characteristicinformation of only a right eye stored in the storage unit 15 for aniris image tagged as right eye, and compares with characteristicinformation of only a left eye stored in the storage unit 15 for an irisimage tagged as left eye. The score calculation unit 16 obtains averification score as a result of the comparison. The verification scoreis a value obtained as a result of calculating the number of bitsdifferent between the iris code of the target user and the iris coderegistered in the storage unit 15 (calculating a hamming distance). Thescore calculation unit 16 weights the detection result by the detectionunit 14 to the verification score, to calculate the first weightedverification score. For example, when the detection unit 14 detects thata region including the left eye and a region including the right eyespecified with the template is overlapped with the region of the leftand right eyes in the divided first image (both eyes overlap at anappropriate position), for example, a calculation result is obtained bymultiplying and adding a predetermined value to the verification score,or substituting into a predetermined formula, in order to increase thevalue of the verification score. In addition, the score calculation unit16 may weight so as to reduce the verification score, when the scorecalculation unit 16 receives a detection result that the left and righteyes do not overlap at an appropriate position.

The authentication unit 17 receives the first weighted verificationscore from the score calculation unit 16, and authenticates the usercaptured in the first image and the second image as a registered user (alegitimate user), for example, when the first weighted verificationscore is equal to or greater than a predetermined threshold value, andauthenticates the user captured in the first image and the second imageas not a registered user when the first weighted verification score isequal to or less than a predetermined threshold value. Theauthentication unit 17 outputs an authentication result to an externaldisplay unit 20. The display unit 20 is a liquid crystal display or thelike, and can display such that the target user or an administrator ofthe authentication execution area can browse the authentication result.In addition, the authentication result may be made known by voicenotification with a speaker or a buzzer, lamp lighting, or the like.

(Operation of Iris Authentication Device)

An operation of the iris authentication device 100 according to thefirst example embodiment will be described with reference to a flowchartof FIG. 10. It is assumed that the storage unit 15 stores, in advance,iris characteristic information of a right eye and a left eye relatingto a plurality of users that may be the authentication target.

In step S101, the first image input unit 11 inputs a first imageobtained by capturing an image of the authentication target user movingin a specific direction. The second image input unit 12 inputs, for atleast one eye, the second image obtained by capturing an image of theright eye or the left eye of the target user.

In step S102, the determination unit 13 determines whether a secondimage is of a left eye or a right eye of the target user on the basis ofinformation including the first image, and outputs left/rightinformation indicating a determination result in association with thesecond image.

In step S103, the detection unit 14 detects an overlap between a regionincluding the second image and a predetermined region in the firstimage.

In step S104, the score calculation unit 16 calculates a verificationscore obtained by comparing iris characteristic information calculatedfrom the second image associated with the left/right information, withone or more pieces of characteristic information related to theleft/right information and stored in the storage unit 15. The scorecalculation unit 16 weights the verification score with a detectionresult, to calculate the first weighted verification score.

In step S105, the authentication unit 17 authenticates the user capturedin the first image and the second image on the basis of the calculatedfirst weighted verification score, and outputs an authentication result.

Thus, the operation of the iris authentication device 100 is ended.

(Effect of First Example Embodiment)

According to the first example embodiment, iris authentication can beperformed by reliably identifying left and right eyes. The reason forthis is because the determination unit 13 determines whether the secondimage is of a left eye or a right eye of the user on the basis ofinformation including the first image, and outputs a determinationresult as the left/right information in association with the secondimage. Further, the reason is because the detection unit 14 detects anoverlap between a region including left and right eyes in a region ofthe face template and a region of left and right eyes in the firstimage, and weights the verification score on the basis of the detectionresult.

Second Example Embodiment

In the first example embodiment, the weights for authentication of theleft and right eyes are the same, but one eye is easy to identify andone eye is difficult to identify since features of the right and leftirises are different even for the same person. Since the eye that iseasy to identify requires less time for authentication processing and ismore accurate in identification, it is possible to performauthentication with higher accuracy in a shorter time by performing theauthentication processing using the eye that is easy to identify amongright and left eyes. In the second example embodiment, a description isgiven to an iris authentication device and the like for performing theauthentication processing by weighting an eye that is easy to identify.

(Iris Authentication Device)

As shown in FIG. 11, an iris authentication device 200 includes a firstimage input unit 11, a second image input unit 12, a determination unit13, a detection unit 14, a storage unit 15 a, a score calculation unit16 a, and an authentication unit 17. The first image input unit 11 andthe second image input unit 12 are connected to an external camera 10.The authentication unit 17 is connected to an external display unit 20.

As shown in FIG. 12, the storage unit 15 a stores characteristicinformation and a reliability score of a right eye and characteristicinformation and a reliability score of a left eye of each user, for eachidentifier (ID) that is associated with a user to be authenticated andcan be identified. The reliability is a value indicating the ease ofidentification between the target user and other users, and thereliability score represents this value by 0 to 100%. An example of acalculation method of the reliability score will be described. Bysetting each ID of a registered user stored in a second storage unit 22as i (i={1, 2, 3, . . . , N}; N is a total number of registered users),characteristic information (a characteristic vector) of an iris image ofa right eye of each registered user as X_(right) (i), and characteristicinformation (a characteristic vector) of an iris image of a right eye ofa current target user (a person desired to be collated) as Y_(right),correlation between X_(right) (i) and Y_(right) (for example, normalizedcross-correlation) is calculated for all registered users i. After thecalculation, calculation is performed on a ratio(=highest correlationvalue/second correlation value) of the largest correlation value (thatis, a correlation value between the same persons (when the target useris hit as a registered user)) to a second correlation value (acorrelation value between the person and a registered user who isanother person with the highest correlation value), and the calculatedvalue is set as reliability S_(right). Similarly, similar processing isperformed for a left eye, and the calculated value is set as reliabilityS_(left). By normalizing these reliabilities S_(right) and S_(left) andconverting to values of 0% to 100%, the reliability score (for example,left eye 20%, right eye 80%) is obtained. While there are variousmethods for normalizing the reliability, for example, the reliabilityscore (%)=100×(S−1)/(M−1) is calculated (where 1≤S≤M; S representseither S_(right) or S_(left), and M represents a maximum value of thereliability. The maximum value is set in advance by a designer or thelike, and the reliability in a case of M<S is 100). The method forcalculating the reliability score is not limited to the above. As thereliability score is higher, characteristic information of the targetuser is easy to be identified (is a rare iris code) as compared withcharacteristic information of other users. For example, in a case of theuser ID “1”, the reliability score of the right eye is 80%, and thereliability score of the left eye is 20%, which indicates that an irisof a right eye of the user is distinctive, and there are relatively nousers having similar characteristic information. Conversely, it isindicated that an iris of the left eye of the user is not verydistinctive, and there are many users having similar characteristicinformation. In such a case, since it is more efficient to use the righteye for the authentication processing, it is desirable to perform theauthentication processing using the second image of the right eye evenwhen the second image of both eyes can be captured. Conversely, if ithas been possible to capture the second image of only the left eye forsome reason, it can be inferred that this is because the reliabilityscore of the left eye is low even if the verification score of theauthentication is low. In this case, the iris authentication device 200can also request the user to capture the iris image again. Specifically,the iris authentication device 200 requests the user to move again froman entrance gate to an exit gate for authentication again via thedisplay unit 20 or the like. If an eye with a higher reliability scoreis hidden by hair and the like, the authentication unit 17 may present,to the display unit 20, text or the like requesting cooperation from theuser so that the eye having the higher reliability score can be clearlycaptured by the camera 10.

In addition to the operation of the score calculation unit 16 shown inFIG. 1, the score calculation unit 16 a performs authentication using asecond weighted verification score obtained by adding the reliabilityscore to the verification score. The score calculation unit 16 acalculates the verification score obtained by comparing irischaracteristic information calculated from the second image associatedwith the left/right information, with one or more pieces ofcharacteristic information related to the left/right information andstored in the storage unit 15 a. Furthermore, the score calculation unit16 a specifies the target user on the basis of the verification score,acquires the reliability score related to the target user from thestorage unit 15 a, and calculates the second weight reference score inwhich the reliability score is reflected on the calculated verificationscore. For example, for a user with ID “1” in FIG. 12, a reliabilityscore of the right eye is 80%, and a reliability score of the left eyeis 20%. Therefore, when the verification score of the second image ofboth eyes has been calculated, the score calculation unit 16 a weightsthe verification score of the right eye with the reliability score ofthe right eye, and weights the verification score of the left eye withthe reliability score of the left eye. At this time, the scorecalculation unit 16 a may increase the priority of the eye having higherreliability, and weight only the verification score of the right eyewith the reliability score of the right eye. This enables a score ofhigher reliability to be obtained. The weighting refers to obtaining acalculation result by multiplying, adding, or substituting both scoresinto a predetermined formula, for example. The score calculation unit 16a transfers the weighted calculation result to the authentication unit17 as the second weighted verification score.

Operations of the other units are similar to those of the first exampleembodiment.

(Operation of Iris Authentication Device)

An operation of the iris authentication device 200 according to thesecond example embodiment will be described with reference to aflowchart of FIG. 13. It is assumed that the storage unit 15 a stores,in advance, iris characteristic information and reliability scores (seeFIG. 12) of a right eye and a left eye relating to a plurality of usersthat may be the authentication target.

Steps S201 to S204 are similar to steps S101 to S104 in FIG. 10.

In step S205, the score calculation unit 16 a specifies the target userfrom the storage unit 15 a on the basis of the verification scorecalculated in step S204, acquires the reliability score related to thetarget user from the storage unit 15 a, and weights the calculatedverification score with the reliability score. At this time, the scorecalculation unit 16 a may give priority to an eye having higherreliability, and weight the verification score of the eye having higherpriority with the reliability score of the eye. The score calculationunit 16 a transfers a second verification score weighted by thereliability score, to the authentication unit 17.

Step S206 is similar to step S105 in FIG. 10.

Thus, the operation of the iris authentication device 200 is ended.

(Effect of Second Example Embodiment)

According to the second example embodiment, authentication processingwith higher accuracy can be performed, in addition to the effects of thefirst example embodiment. The reason for this is because the scorecalculation unit 16 a specifies the target user from the storage unit 15a on the basis of the calculated verification score, acquires thereliability score related to the target user from the storage unit 15 a,and weights the calculated verification score with the reliabilityscore. Further, the reason is because the score calculation unit 16 agives priority to an eye having higher reliability, and weights theverification score of the eye having higher priority with thereliability score of the eye.

<Third Example Embodiment>

In the first and second example embodiments, only iris authenticationusing the second image is performed. However, another biometricauthentication (human form authentication, gait authentication, faceauthentication, or the like) may be performed using the first image, andmultimodal authentication may be performed by combining results of thetwo authentications. This can further improve the accuracy ofauthentication. In a third example embodiment, an iris authenticationdevice and the like for combining another biometric authentication willbe described. The human form authentication refers to authenticationperformed on the basis of physical characteristics (for example, aheight, a body width, a length of limbs, a facial contour, or acombination thereof) of a person to be authenticated.

(Iris Authentication Device)

An iris authentication device 300 includes, as shown in FIG. 14, a firstimage input unit 11, a second image input unit 12, a determination unit13, a detection unit 14, a storage unit 15 a, a score calculation unit16 a, an authentication unit 17 a, a second score calculation unit 21, asecond storage unit 22, and a score integration unit 23. The first imageinput unit 11 and the second image input unit 12 are connected to anexternal camera 10. The authentication unit 17 a is connected to anexternal display unit 20.

The second storage unit 22 stores information (characteristicinformation of a human form, a gait, a face, or the like) to be used forauthentication of another biometric authentication (human formauthentication, gait authentication, face authentication, or the like)using a first image.

The second score calculation unit 21 calculates characteristicinformation of a user to be authenticated from the first image as thesecond verification score, for the other biometric authentication.

The biometric authentication to be used by the second score calculationunit 21 may be initially set or may be set by the user. For example,when the first image is a static image or a moving image obtained bycapturing an image of a whole body of the user, the second scorecalculation unit 21 calculates the second verification score byperforming human form authentication using the static image or gaitauthentication using the moving image. When the first image is an imageobtained by capturing an image of a face of the user, the second scorecalculation unit 21 calculates the second verification score byperforming face authentication using the first image.

The score integration unit 23 integrates the second weightedverification score outputted from the score calculation unit 16 a withthe second verification score outputted from the second scorecalculation unit 21, and outputs as an integrated score to theauthentication unit 17 a. In the integration processing, the integratedscore is calculated by multiplying, adding, or substituting the weightedverification score and the second verification score into apredetermined formula. The second verification score may be integratedto the first weighted verification score outputted by the scorecalculation unit 16 shown in FIG. 1.

The authentication unit 17 a uses the integrated score to performauthentication processing.

Operations of the other units are similar to those of the first andsecond example embodiments.

(Operation of Iris Authentication Device)

An operation of the iris authentication device 300 according to thethird example embodiment will be described with reference to a flowchartof FIG. 15. The storage unit 15 a stores, in advance, irischaracteristic information of a right eye and a left eye relating to aplurality of users that may be the authentication target. Further, areliability score (see FIG. 12) may be stored. The second storage unit22 stores, in advance, body characteristic information relating to aplurality of users that may be the authentication target.

Steps 5301 to 5305 are similar to steps 5201 to 5205 in FIG. 13.

In step S306, the second score calculation unit 21 performs biometricauthentication (human form authentication, gait authentication, faceauthentication, or the like) other than iris authentication by using afirst image in which a user's body image is captured, calculatescharacteristic information of the user's body included in the firstimage, compares the calculated characteristic information with thecharacteristic information stored in the second storage unit 22, andoutputs a comparison result to the score integration unit 23 as thesecond verification score.

In step S307, the score integration unit 23 calculates an integratedscore obtained by adding the second verification score outputted by thesecond score calculation unit 21 to the second weighted verificationscore outputted by the score calculation unit 16 a. The scoreintegration unit 23 outputs the calculated integrated score to theauthentication unit 17 a.

In step S308, the authentication unit 17 a authenticates the usercaptured in the first image and the second image on the basis of thecalculated integrated score, and outputs an authentication result.Specifically, the authentication unit 17 a authenticates the usercaptured in the first image and the second image as a registered user (alegitimate user), for example, when the integrated score is equal to orgreater than a predetermined threshold, and authenticates the usercaptured in the first image and the second image as not a registereduser when the integrated score is equal to or less than a predeterminedthreshold value. Then, the authentication unit 17 a outputs theauthentication result to an external display unit 20.

Thus, the operation of the iris authentication device 300 is ended.

(Effect of Third Example Embodiment)

According to the third example embodiment, it is possible to provide theiris authentication device 300 having even higher authenticationaccuracy than the iris authentication devices described in the first tosecond example embodiments. The reason for this is because the secondscore calculation unit 21 calculates characteristic information from abody image of the authentication target user included in the first imageand outputs the second verification score, the score integration unit 23calculates an integrated score in which the second verification score isreflected on the second weighted verification score, and theauthentication unit 17 a performs the authentication processing on thebasis of this integrated score. The score integration unit 23 may bedesigned to reflect the second verification score on the first weightedverification score to calculate the integrated score.

<Fourth Example Embodiment>

In the detection by the detection unit 14, when an image of a movingtarget user is captured from the camera 10 at a predetermined position,a machine learning engine is made to learn which rectangular region inthe first image includes left and right eyes on the basis of teacherdata before operation of the iris authentication device, and a designeror the like sets a position of the camera 10 on the basis of a learningresult. However, it is desirable to cause the machine learning enginefor authentication to learn by using history data after operation of theiris authentication device, and to feed back points to be improved toeach part of the iris authentication device.

For example, after operation, the machine learning engine can learnwhere, what, and how images appear on a screen captured by the fixedcamera 10, and a position, an angle, and the like of the camera 10 canbe adjusted on the basis of the learning result. This can be learned andadjusted by the machine learning engine on the basis mainly of a historyof authentication result data when the authentication is successful.

Even an image captured by the fixed camera 10 may have differentauthentication accuracy depending on a season and time. For example,authentication accuracy may be high in the morning but authenticationaccuracy may be low in the afternoon, or authentication accuracy may behigh in the daytime but authentication accuracy may be low at night.This is often caused by a change in light applied to the target userwhile the camera 10 is capturing an image. In addition to this, anotherpossible cause is that types of teacher data used for the learning ofthe machine learning engine have been biased (for example, only imagescaptured in the morning have been learned). This can be learned andadjusted by the machine learning engine on the basis mainly of a historyof authentication result data when the authentication fails.

Depending on a lighting condition of the target user at the time ofcapturing an image by the camera 10, there is a change in a luminancevalue of a pixel in a region of a whole body or a face of the user inthe first image, and a luminance value of a pixel in a region of leftand right eyes of the user in the second image. The light may be outdoorlight (sunlight), indoor light (illumination light), or a mixturethereof. Sunlight reaching a ground surface changes in accordance with aseason of image capturing and progress of time of image capturing. Theindoor light changes with illuminance, orientation, and a type ofillumination, as well as addition or reduction of illumination. In acase of authentication in a mixed area of sunlight and indoor light,both should be taken into account. In a fourth example embodiment, adescription is given to an iris authentication device and the like forperforming feedback adjustment on the basis of a history ofauthentication result data after operation, as described above.

(Iris Authentication Device)

An iris authentication device 400 includes, as shown in FIG. 16, a firstimage input unit 11, a second image input unit 12, a determination unit13, a detection unit 14, a storage unit 15 a, a score calculation unit16 a, an authentication unit 17, an authentication result storage unit31, a learning unit 32, and a feedback unit 33. The first image inputunit 11 and the second image input unit 12 are connected to an externalcamera 10. The authentication unit 17 is connected to an externaldisplay unit 20.

The authentication result storage unit 31 stores authentication resultdata obtained by the authentication unit 17 (see FIG. 17). Theauthentication result data includes, as items, for example, anauthentication ID, an authentication time, an authentication result, andauthentication image data. The authentication ID is an ID foridentifying each authentication result. The authentication time is thetime when the authentication result is calculated. The authenticationresult is a code, a value, or the like representing a result ofauthentication. As shown in FIG. 17, the authentication result indicates“∘” for a legitimate user, and “×” for not a legitimate user. These areall authentication success data. When authentication fails but the useris a legitimate user, an ID of the legitimate user is stored (forexample, in FIG. 17, an ID “1234” of a legitimate user for theauthentication ID “1”, and an ID “5678” of a legitimate user for theauthentication ID “5”). The ID of the legitimate user is read from atouch panel, a scanner, or the like (not shown) by a user or a manager.When the authentication fails but the user is a legitimate user, thedata is to be authentication failure data. A method for specifying theauthentication failure data is not limited to the above. For example,when an observer is shown in an image captured by the camera 10, it maybe regarded that some trouble has occurred in the authenticationprocessing, and the data may be made authentication failure data.Whether the observer is shown is determined by face authentication ofthe observer or by authentication of a mark indicating the observer onthe observer's clothing (back, an arm, or the like). In addition, byinstalling an iris authentication device higher in accuracy than theiris authentication device 400 at the same position, authenticationfailure data can also be extracted by comparing the two authenticationresult data.

The learning unit 32 learns which rectangular region in a first imageincludes a pixel indicating a left eye and a right eye, on the basis ofthe authentication result data extracted from the authentication resultstorage unit 31. This is for feedback to the detection unit 14 whichrectangular region in the first image includes a left eye and a righteye more often.

Further, the learning unit 32 learns characteristics of light includedin the first image and a second image, and determines, in a specificperiod, which of the left eye or the right eye of the target user shouldbe associated with the second image as left/right information. Thecharacteristics of light include a change in a luminance value of apixel indicating the target user in the first image and the secondimage. The change in the luminance value includes a change in sunlightalong seasonal and time transitions at a particular location, as well asa change in a type of a light source and arrangement of the light sourcein a room. The learning unit 32 learns how the characteristics of lightaffect the luminance value of the pixel indicating the target user, anddetermines the camera 10 to be used for authentication and left andright eyes to be used for authentication for each date and time, on thebasis of a learning result.

The learning unit 32 includes a machine learning engine or the like thatlearns on the basis of authentication result data stored in theauthentication result storage unit 31. The learning unit 32 may bedesigned to be connected to an external machine learning engine andreceive results of learning.

For example, for obtaining feedback about adjustment of a position or anangle of the camera 10, the learning unit 32 learns on the basis mainlyof a history of the authentication success data, and outputs informationabout a camera position and an angle for accommodating a region of theface of the target user in the first or second image. In a case wherethere are a plurality of fixed cameras 10, for obtaining feedback onwhich camera 10 to be used in accordance with a season or time of day,the learning unit 32 learns on the basis mainly of a history of theauthentication failure data, and outputs information for determining avideo image captured by which camera 10 is suitable, based on a lightcondition of a current authentication area. Even when irisauthentication is performed on the basis of an image captured by thefixed camera 10, the authentication accuracy of the left and right eyesmay be changed in the morning and afternoon by a change in sunlight. Insuch a case, as shown in FIG. 18, the learning unit 32 outputsinformation that authentication should be performed on the basis of theright eye of the target user in the morning, and authentication shouldbe performed on the basis of the left eye of the target user in theafternoon (it is assumed that target user is moving northward). Further,when the learning unit 32 learns that the authentication accuracy tendsto decrease at night due to bias of teacher data of the machine learningengine to be used, the learning unit 32 outputs information on types ofteacher data to be additionally learned and the like. The learning unit32 transfers the learning result to the feedback unit 33, and alsodisplays the learning result on the display unit 20.

On the basis of the learning result, the feedback unit 33 adjustsoperations of the camera 10, the first image input unit 11, the secondimage input unit 12, the determination unit 13, the detection unit 14,the score calculation unit 16 a, and the authentication unit 17. Anadministrator or the like may manually adjust each unit on the basis ofthe learning result displayed on the display unit 20.

Operations of the other units are similar to those of the first andsecond example embodiments.

(Operation of Iris Authentication Device)

An operation of the iris authentication device 400 according to thefourth example embodiment will be described with reference to aflowchart of FIG. 19. It is assumed that the storage unit 15 a stores,in advance, iris characteristic information and reliability scores (seeFIG. 12) of a right eye and a left eye relating to a plurality of usersthat may be the authentication target.

Steps S401 to S406 are similar to steps S201 to S206 in FIG. 13.

In step S407, the learning unit 32 learns which rectangular region inthe first image includes a pixel indicating a left eye and a right eye,on the basis of the authentication result data extracted from theauthentication result storage unit 31. Further, the learning unit 32learns characteristics of light included in the first image, anddetermines, in a specific period, which of the left eye or the right eyeof the target user should be associated with the second image asleft/right information. This learning may be performed after theauthentication result data is accumulated up to a predetermined amount.

In step S408, the learning unit 32 determines whether the learningresult should be presented to the display unit 20, or fed back to eachunit of the iris authentication device 400. The designer may determinein advance, or the learning unit 32 may determine with what kind oftrigger or timing the feedback should be made. When it is determinedthat feedback should be made, the process proceeds to step S409, andwhen it is determined that feedback should not be made yet, the processreturns to step S401.

In step S408, when receiving the learning result from the learning unit32, the feedback unit 33 feeds back the learning result to each unit ofthe iris authentication device 400 to urge adjustment as appropriate.

Thus, the operation of the iris authentication device 400 is ended.

(Effect of Fourth Example Embodiment)

According to the fourth example embodiment, authentication processingwith higher accuracy can be performed, in addition to the effects of thefirst and second example embodiments. The reason for this is because thelearning unit 32 learns, on the basis of the history of theauthentication result data, which rectangular region in the first imageincludes a pixel indicating a left eye and a right eye, and learnscharacteristics of light included in the first and second images.Further, the learning result is fed back to each unit of the irisauthentication device 400. This enables authentication with higheraccuracy to be performed in accordance with operation of the irisauthentication device.

Meanwhile, the example embodiments each may be used in combination.

(Information Processing Apparatus)

In each of the example embodiments described above, some or all of theindividual components of the iris authentication device shown in FIGS.1, 11, 14, 16, and the like may be implemented by using any combinationof, for example, an information processing apparatus 500 as shown inFIG. 20 and a program. The information processing apparatus 500includes, as an example, the following configuration.

A central processing unit (CPU) 501

A read only memory (ROM) 502

A random access memory (RAM) 503

A storage device 505 that stores a program 504 and other data

A drive device 507 that reads from and writes into a recording medium506

A communication interface 508 that connects to a communication network509

An input-output interface 510 to input and output data

A bus 511 that connects individual components

Individual components of the iris authentication device in each exampleembodiment of the application are implemented by the CPU 501 obtainingand executing the program 504 for achieving these functions. The program504 for achieving the functions of the individual components of the irisauthentication device is stored in advance, for example, in the storagedevice 505 or the RAM 503, and is read out by the CPU 501, as necessary.The program 504 may be supplied via the communication network 509 to theCPU 501, or may be stored in advance in the recording medium 506 andsupplied to the CPU 501 by the drive device 507 reading out the program.

There are various modifications for a method of implementing eachdevice. For example, the iris authentication device may be implementedby any combination of an information processing apparatus and a programthat are separate for each component. Further, a plurality of componentsincluded in the iris authentication device may be implemented by anycombination of one information processing apparatus 500 and a program.

Furthermore, some or all of the individual components of the irisauthentication device may be implemented by other general-purpose ordedicated circuit, processor, and the like, or a combination thereof.These may be configured by a single chip or a plurality of chipsconnected via a bus.

Some or all of the individual components of the iris authenticationdevice may be implemented by a combination of the above-describedcircuit and the like and a program.

In a case where some or all of the individual components of the irisauthentication device are implemented by a plurality of informationprocessing apparatuses, circuits, and the like, the plurality ofinformation processing apparatuses, circuits, and the like, may becentrally arranged or dispersedly arranged. For example, the informationprocessing apparatus, the circuit, and the like may be implemented as aform in which each is connected via a communication network, such as aclient and server system, a cloud computing system, and the like.

The whole or part of the example embodiments disclosed above can bedescribed as, but not limited to, the following supplementary notes.

[Supplementary Note 1]

An iris authentication device comprising:

a first image input means for inputting a first image obtained bycapturing an image of an authentication target that moves in a specificdirection;

a second image input means for inputting, for at least one eye, a secondimage obtained by capturing an image of a right eye or a left eye of thetarget;

a determination means for determining whether the second image is of aleft eye or a right eye of the target on the basis of informationincluding the first image, and outputting a determination result asleft/right information in association with the second image;

a detection means for detecting an overlap between a region includingthe second image and a predetermined region in the first image;

a storage means for storing iris characteristic information of a righteye and a left eye relating to one or more targets to be authenticated;

a score calculation means for calculating a verification score bycomparing iris characteristic information calculated from the secondimage associated to the left/right information, with one or more piecesof characteristic information that are related to the left/rightinformation and stored in the storage means, and calculating a firstweighted verification score obtained by weighting the calculatedverification score with a result of the detection; and

an authentication means for authenticating a target captured in thesecond image on the basis of the calculated first weighted verificationscore, and outputting an authentication result.

[Supplementary Note 2]

The iris authentication device described in Supplementary Note 1, inwhich

the storage means stores a reliability score of a right eye and a lefteye relating to the targets to be authenticated,

the score calculation means specifies the target on the basis of theverification score, acquires the reliability score related to the targetfrom the storage means, and calculates a second weighted verificationscore obtained by weighting the verification score with the reliabilityscore.

[Supplementary Note 3]

The iris authentication device described in Supplementary Note 1 or 2,in which

the score calculation means calculates the second weighted verificationscore with priority given to an eye having a higher value indicating thereliability score.

[Supplementary Note 4]

The iris authentication device according to any one of SupplementaryNotes 1 to 3, further comprising:

a second storage means for storing characteristic information calculatedfrom a body image of one or more targets to be authenticated;

a second score calculation means for calculating characteristicinformation from a body image of the target included in the first imageacquired from the first image input means, comparing the calculatedcharacteristic information with characteristic information stored in thesecond storage means, and outputting a comparison result as a secondverification score; and

a score integration means for calculating an integrated score reflectingthe second verification score outputted by the second score calculationmeans on the first weighted verification score or the second weightedverification score outputted by the score calculation means, in which

the authentication means authenticates the target captured in the secondimage on the basis of the first weighted verification score, the secondweighted verification score, or the integrated score, and outputs anauthentication result.

[Supplementary Note 5]

The iris authentication device described in Supplementary Note 4, inwhich

the first image is a static image or a moving image obtained bycapturing an image of a whole body of the target, and the second scorecalculation means calculates characteristic information of the bodyimage by executing human form authentication using the static image orgait authentication using the moving image.

[Supplementary Note 6]

The iris authentication device described in Supplementary Note 4, inwhich

the first image is an image obtained by capturing an image of a face ofthe target, and the second score calculation means calculatescharacteristic information of the body image by executing faceauthentication using the first image.

[Supplementary Note 7]

The iris authentication device described in Supplementary Note 1, inwhich

the determination means applies a predetermined template to a region ofa face of the target in the first image, and determines whether the twoimages are relevant to a left eye or a right eye of the target.

[Supplementary Note 8]

The iris authentication device described in Supplementary Note 1, inwhich

the determination means compares a pixel in a region of a right eye anda left eye of the target in the first image with a pixel in a region ofa right eye or a left eye of the target in the second image, anddetermines whether the two images are relevant to a left eye or a righteye of the target.

[Supplementary Note 9]

The iris authentication device described in Supplementary Note 1, inwhich

the predetermined region is one region in the first image divided into aplurality of regions,

the iris authentication device further comprising:

an authentication result storage means for storing data of theauthentication result; and

a learning means for learning which of the regions in the first imageincludes a pixel indicating a left eye and a right eye on the basis ofdata of the authentication result extracted from the authenticationresult storage means, and setting, as the predetermined region, each ofa region of a left eye and a region of a right eye that have beenlearned.

[Supplementary Note 10]

The iris authentication device described in Supplementary Note 9, inwhich

the learning means learns characteristics of light included in the firstimage and the second image on the basis of data of the authenticationresult extracted from the authentication result storage means, anddetermines which of a left eye or a right eye of the target should beassociated with the second image as the left/right information in aspecific period.

[Supplementary Note 11]

The iris authentication device described in Supplementary Note 10, inwhich

the characteristics of light include a change in a luminance value of apixel indicating a user as the target in the first image and the secondimage.

[Supplementary Note 12]

The iris authentication device described in Supplementary Note 11, inwhich

a change in the luminance value includes a change in sunlight alongseasonal and time transitions at the particular location, as well as achange in a type of a light source and arrangement of the light sourcein a room.

[Supplementary Note 13]

An iris authentication method comprising:

inputting a first image obtained by capturing an image of anauthentication target that moves in a specific direction;

inputting, for at least one eye, a second image obtained by capturing animage of a right eye or a left eye of the target;

determining whether the second image is of a left eye or a right eye ofthe target on the basis of information including the first image, andoutputting a determination result as left/right information inassociation with the second image;

detecting an overlap between a region including the second image and apredetermined region in the first image;

calculating a verification score by comparing one or more pieces ofcharacteristic information that are related to the left/rightinformation and acquired from a storage means for storing irischaracteristic information of a right eye and a left eye relating to oneor more targets to be authenticated, with iris characteristicinformation calculated from the second image associated to theleft/right information, and calculating a first weighted verificationscore obtained by weighting the calculated verification score with aresult of the detection; and

authenticating a target captured in the second image on the basis of thecalculated first weighted verification score, and outputting anauthentication result.

[Supplementary Note 14]

The iris authentication method described in Supplementary Note 13, inwhich

the storage means stores a reliability score of a right eye and a lefteye relating to the targets to be authenticated, and

in calculating the first weighted verification score, the target isspecified on the basis of the verification score, the reliability scorerelated to the target is acquired from the storage means, and a secondweighted verification score obtained by weighting the verification scorewith the reliability score is calculated.

[Supplementary Note 15]

The iris authentication method described in Supplementary Note 13 or 14,in which

in calculating the first weighted verification score, the secondweighted verification score is calculated with priority given to an eyehaving a higher value indicating the reliability score.

[Supplementary Note 16]

The iris authentication method described in any one of SupplementaryNotes 13 to 15, further comprising:

calculating characteristic information from a body image of the targetincluded in the acquired first image, comparing the calculatedcharacteristic information with characteristic information stored in asecond storage means for storing characteristic information calculatedfrom a body image of one or more targets to be authenticated, andoutputting a comparison result as a second verification score; and

calculating, in calculating the first weighted verification score, anintegrated score reflecting the second verification score on the firstweighted verification score or the second weighted verification score,in which

authenticating the target and outputting an authentication resultinclude authenticating a target captured in the second image on thebasis of the first weighted verification score, the second weightedverification score, or the integrated score, and outputting anauthentication result.

[Supplementary Note 17]

The iris authentication method described in Supplementary Note 16, inwhich

the first image is a static image or a moving image obtained bycapturing an image of a whole body of the target, and outputting thecomparison result as a second verification score includes calculatingcharacteristic information of the body image by executing human formauthentication using the static image or gait authentication using themoving image.

[Supplementary Note 18]

The iris authentication method described in Supplementary Note 16, inwhich

the first image is an image obtained by capturing an image of a face ofthe target, and outputting the comparison result as a secondverification score includes calculating characteristic information ofthe body image by executing face authentication using the first image.

[Supplementary Note 19]

The iris authentication method described in Supplementary Note 13, inwhich

in outputting the determination result as left/right information inassociation with the second image, a predetermined template is appliedto a region of a face of the target in the first image, and it isdetermined whether the two images are relevant to a left eye or a righteye of the target.

[Supplementary Note 20]

The iris authentication method described in Supplementary Note 13, inwhich

in outputting the determination result as left/right information inassociation with the second image, a pixel in a region of a right eyeand a left eye of the target in the first image is compared with a pixelin a region of a right eye or a left eye of the target in the secondimage, and it is determined whether the two images are relevant to aleft eye or a right eye of the target.

[Supplementary Note 21]

The iris authentication method described in Supplementary Note 13, inwhich

the predetermined region is one region in the first image divided into aplurality of regions,

the iris authentication method further comprising:

learning which of the regions in the first image includes a pixelindicating a left eye and a right eye on the basis of data of theauthentication result extracted from an authentication result storagemeans for storing data of the authentication result, and setting, as thepredetermined region, each of a region of a left eye and a region of aright eye that have been learned.

[Supplementary Note 22]

The iris authentication method described in Supplementary Note 21, inwhich

the learning includes learning characteristics of light included in thefirst image and the second image on the basis of data of theauthentication result extracted from the authentication result storagemeans, and determining which of a left eye or a right eye of the targetshould be associated with the second image as the left/right informationin a specific period.

[Supplementary Note 23]

The iris authentication method described in Supplementary Note 22, inwhich

the characteristics of light includes a change in a luminance value of apixel indicating a user as the target in the first image and the secondimage.

[Supplementary Note 24]

The iris authentication method described in Supplementary Note 23, inwhich

a change in the luminance value includes a change in sunlight alongseasonal and time transitions at the particular location, as well as achange in a type of a light source and arrangement of the light sourcein a room.

[Supplementary Note 25]

A recording medium storing an iris authentication program for causing acomputer to enable:

inputting a first image obtained by capturing an image of anauthentication target that moves in a specific direction;

inputting, for at least one eye, a second image obtained by capturing animage of a right eye or a left eye of the target;

determining whether the second image is of a left eye or a right eye ofthe target on the basis of information including the first image, andoutputting a determination result as left/right information inassociation with the second image;

detecting an overlap between a region including the second image and apredetermined region in the first image;

calculating a verification score by comparing one or more pieces ofcharacteristic information that are related to the left/rightinformation and acquired from a storage means for storing irischaracteristic information of a right eye and a left eye relating to oneor more targets to be authenticated, with iris characteristicinformation calculated from the second image associated to theleft/right information, and calculating a first weighted verificationscore obtained by weighting the calculated verification score with aresult of the detection; and

authenticating a target captured in the second image on the basis of thecalculated first weighted verification score, and outputting anauthentication result.

[Supplementary Note 26]

The recording medium as described in Supplementary Note 25, in which

the storage means stores a reliability score of a right eye and a lefteye relating to the targets to be authenticated,

in calculating the first weighted verification score, the target isspecified on the basis of the verification score, the reliability scorerelated to the target is acquired from the storage means, and a secondweighted verification score obtained by weighting the verification scorewith the reliability score is calculated.

[Supplementary Note 27]

The recording medium as described in Supplementary Note 25 or 26, inwhich

in calculating the first weighted verification score, the secondweighted verification score is calculated with priority given to an eyehaving a higher value indicating the reliability score.

[Supplementary Note 28]

The recording medium as described in any one of Supplementary Notes 25to 27, the iris authentication program further comprising:

calculating characteristic information from a body image of the targetincluded in the first image acquired from the first image input means,comparing the calculated characteristic information with characteristicinformation stored in a second storage means for storing characteristicinformation calculated from a body image of one or more targets to beauthenticated, and outputting a comparison result as a secondverification score; and

calculating, in calculating the first weighted verification score, anintegrated score reflecting the second verification score on the firstweighted verification score or the second weighted verification score,in which

authenticating the target and outputting an authentication resultinclude authenticating a target captured in the second image on thebasis of the first weighted verification score, the second weightedverification score, or the integrated score, and outputting anauthentication result.

[Supplementary Note 29]

The recording medium as described in Supplementary Note 28, in which

the first image is a static image or a moving image obtained bycapturing an image of a whole body of the target, and outputting thecomparison result as a second verification score includes calculatingcharacteristic information of the body image by executing human formauthentication using the static image or gait authentication using themoving image.

[Supplementary Note 30]

The recording medium as described in Supplementary Note 28, in which

the first image is an image obtained by capturing an image of a face ofthe target, and outputting the comparison result as a secondverification score includes calculating characteristic information ofthe body image by executing face authentication using the first image.

[Supplementary Note 31]

The recording medium as described in Supplementary Note 25, in which

in outputting the determination result as left/right information inassociation with the second image, a predetermined template is appliedto a region of a face of the target in the first image, and it isdetermined whether the two images are relevant to a left eye or a righteye of the target.

[Supplementary Note 32]

The recording medium as described in Supplementary Note 25, in which

in outputting the determination result as left/right information inassociation with the second image, a pixel in a region of a right eyeand a left eye of the target in the first image is compared with a pixelin a region of a right eye or a left eye of the target in the secondimage, and it is determined whether the two images are relevant to aleft eye or a right eye of the target.

[Supplementary Note 33]

The recording medium as described in Supplementary Note 25, in which

the predetermined region is one region in the first image divided into aplurality of regions,

the iris authentication program further comprising:

learning which of the regions in the first image includes a pixelindicating a left eye and a right eye on the basis of data of theauthentication result extracted from an authentication result storagemeans for storing data of the authentication result, and setting, as thepredetermined region, each of a region of a left eye and a region of aright eye that have been learned.

[Supplementary Note 34]

The recording medium as described in Supplementary Note 33, in which

the learning includes learning characteristics of light included in thefirst image and the second image on the basis of data of theauthentication result extracted from the authentication result storagemeans, and determining which of a left eye or a right eye of the targetshould be associated with the second image as the left/right informationin a specific period.

[Supplementary Note 35]

The recording medium as described in Supplementary Note 34, in which

the characteristics of light include a change in a luminance value of apixel indicating a user as the target in the first image and the secondimage.

[Supplementary Note 36]

The recording medium as described in Supplementary Note 35, in which

a change in the luminance value includes a change in sunlight alongseasonal and time transitions at the particular location, as well as achange in a type of a light source and arrangement of the light sourcein a room.

While the disclosure has been particularly shown and described withreference to exemplary embodiments thereof, the disclosure is notlimited to these embodiments. It will be understood by those of ordinaryskill in the art that various changes in form and details may be madetherein without departing from the spirit and scope of the exampleembodiments as defined by the claims.

REFERENCE SIGNS LIST

-   10 camera-   11 first image input unit-   12 second image input unit-   13 determination unit-   14 detection unit-   15 storage unit-   15 a storage unit-   16 score calculation unit-   16 a score calculation unit-   17 authentication unit-   17 a authentication unit-   20 display unit-   21 second score calculation unit-   22 second storage unit-   23 score integration unit-   31 authentication result storage unit-   32 learning unit-   33 feedback unit-   100 iris authentication device-   200 iris authentication device-   300 iris authentication device-   400 iris authentication device-   500 information processing apparatus-   501 CPU-   503 RAM-   504 program-   505 storage device-   506 recording medium-   507 drive device-   508 communication interface-   509 communication network-   510 input-output interface-   511 bus-   507 drive device-   508 communication interface-   509 communication network-   510 input-output interface-   511 bus

1. An authentication device comprising: a memory configured to storeinstructions; and at least one processor configured to execute theinstructions to: acquire a first image by capturing an authenticationtarget, the authentication target being moving in a predetermineddirection; acquire a second image from a plurality of images bycapturing a left eye or a right eye of the authentication target, thesecond image including the brighter of the left eye and the right eye ofthe authentication target; determine whether the eye included in thesecond image is of the left eye or the right eye of the authenticationtarget using the first image; calculate a first verification score bycomparing characteristic information on an iris of the eye in the secondimage with one or more sets of characteristic information about irisesof eyes in a plurality of registrants stored in a storage, each of theplurality of registrants being an object to be authenticated;authenticate the authentication target using the first verificationscore; and output an authentication result.
 2. The authentication deviceaccording to claim 1, wherein the at least one processor is furtherconfigured to execute the instructions to: detect an overlap between aregion including the second image and a predetermined region in thefirst image; calculate a first weighted verification score by weightingthe calculated first verification score with a result of detection aboutthe overlap; and authenticate the authentication target using the firstweighted verification score instead of the first verification score. 3.The authentication device according to claim 1, wherein a plurality ofreliability scores of right eyes and left eyes pertaining to each of theplurality of registrants are stored in the storage, and wherein the atleast one processor is further configured to execute the instructionsto: specify the authentication target based on the first verificationscore; calculate a second weighted verification score by weighting thefirst verification score with a reliability score, the reliability scorestored in the storage with respect to the specified authenticationtarget; and authenticate the authentication target using the secondweighted verification score instead of the first verification score. 4.The authentication device according to claim 3, wherein the at least oneprocessor calculates the second weighted verification score using thehigher of the reliability score of the left eye and reliability score ofthe right eye with respect to the authentication target.
 5. Theauthentication device according to claim 2, wherein the first imageincludes a body image of the authentication target, wherein the storagestores a plurality of sets of characteristic information calculated froma plurality of body images pertaining to each of the plurality ofregistrants, and wherein the at least one processor is furtherconfigured to execute the instructions to: calculate characteristicinformation from the body image of the authentication target included inthe first image; calculate a second verification score by comparing thecalculated characteristic information on the body image of theauthentication target with one or more sets of the characteristicinformation of others stored in the storage; calculate an integratedscore by the second verification score being reflected on the firstweighted verification score with respect to the authentication target;and authenticate the authentication target using the integratedverification score instead of the first weighted verification score. 6.The authentication device according to claim 5, wherein the first imageis a static image or a moving image by capturing a whole body of theauthentication target, and wherein the at least one processor calculatesthe characteristic information on the body image by executing a humanshape authentication using the static image or a gait authenticationusing the moving image.
 7. The authentication device according to claim1, wherein the at least one processor specifies and acquires the secondimage using information including a capturing date and time and a movingdirection of the authentication target.
 8. The authentication deviceaccording to claim 1, wherein the at least one processor specifies andacquires the second image using a learning result of learningcharacteristics of light, the characteristics of light ischaracteristics relating to luminance in the first image and the secondimage.
 9. An authentication method comprising: by at least oneprocessor, acquiring a first image by capturing an authenticationtarget, the authentication target being moving in a predetermineddirection; acquiring a second image from a plurality of images bycapturing a left eye or a right eye of the authentication target, thesecond image including the brighter of the left eye and the right eye ofthe authentication target; determining whether the eye included in thesecond image is of a left eye or a right eye of the authenticationtarget using the first image; calculating a first verification score bycomparing characteristic information on an iris of the eye in the secondimage with one or more sets of characteristic information about irisesof eyes in a plurality of registrants stored in a storage, each of theplurality of registrants being an object to be authenticated;authenticating the authentication target using the first verificationscore; and outputting an authentication result.
 10. A non-transitorystorage medium storing a computer program for causing a computer toimplement: acquiring a first image by capturing an authenticationtarget, the authentication target being moving in a predetermineddirection; acquiring a second image from a plurality of images bycapturing a left eye or a right eye of the authentication target, thesecond image including the brighter of the left eye and the right eye ofthe authentication target; determining whether the eye included in thesecond image is of a left eye or a right eye of the authenticationtarget using the first image; calculating a first verification score bycomparing characteristic information on an iris of the eye in the secondimage with one or more sets of characteristic information about irisesof eyes in a plurality of registrants stored in a storage, each of theplurality of registrants being an object to be authenticated;authenticating the authentication target using the first verificationscore; and outputting an authentication result.